Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any
Installs just this skill. Get the whole plugin for auto-invocation.
⚡ How it fires
How this skill gets triggered: by you, by Claude, or both.
Fires itselfClaude auto-loads it when your prompt matches the work.
You can call itInvoke it directly when you want it.
Slash command/chaos-engineering
👁️ Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any
📊 Stats
Stars23,056
Forks3,139
LanguagePython
LicenseMIT
📦 Ships with claude-skills
</> SKILL.md
chaos-engineering.SKILL.md
---name: chaos-engineering
description: Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question. Ships experiment designer, blast-radius calculator, and postmortem generator (all stdlib Python), 4 references on chaos principles + experiment design + attack taxonomy + tooling landscape, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (common chaos targets).
context: fork
version: 2.9.0
author: claude-code-skills
license: MIT
tags: [chaos-engineering, resilience, fault-injection, gameday, sre, reliability, chaos-toolkit, chaos-mesh, litmus, gremlin, aws-fis]
compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---# Chaos Engineering
Design experiments that surface real weaknesses in production systems — without becoming outages. Most "chaos engineering" attempts skip steady-state measurement, define no abort criteria, and have no blast-radius bound. This skill enforces the discipline that makes chaos experiments safe and useful.
## When to use
- Planning a chaos experiment (what to break, where, when, how to abort)
- Calculating blast radius before running the experiment
Generates a structured experiment plan from inputs. Enforces the required sections (hypothesis, steady-state metric, blast radius, abort criteria, rollback).
```bash
python scripts/experiment_designer.py \
--target "checkout-svc" \
--hypothesis "p99 latency stays <500ms when payment-svc is slow" \
--attack latency \
--magnitude "+200ms" \
--duration-min 15 \
--blast-radius "5% of US traffic" \
--abort-if "p99 > 1000ms OR error_rate > baseline + 1pp"
```
Outputs a markdown plan with: hypothesis, steady-state, attack, magnitude, duration, blast radius, abort criteria, rollback procedure, monitoring dashboards, and learning question.
### `blast_radius_calculator.py`
Computes the blast radius of a planned experiment. Given traffic share + user population + duration, calculates expected affected users, expected error budget burn, and a risk score.
```bash
python scripts/blast_radius_calculator.py \
--traffic-share 0.05 \
--user-pop 1000000 \
--duration-min 15 \
--baseline-availability 0.999 \
--expected-impact-availability 0.95
```
Outputs:
- Expected affected users
- Error budget consumed (in minutes of error budget)
- Risk score: GREEN / YELLOW / RED
- Recommendation: PROCEED / REDUCE / ABORT
GREEN = <1% error budget; YELLOW = 1-10%; RED = >10%.
### `experiment_postmortem.py`
Produces a structured postmortem from an experiment plan + results. Catches the common postmortem failure modes: no learning recorded, no follow-up actions, blame-laden language.
Outputs markdown with: summary, hypothesis (was it confirmed/refuted?), what we learned, what surprised us, follow-up actions with owners, and link to next experiment.
## The 7 attack types (taxonomy)
Different attacks reveal different weaknesses. See `references/attack_taxonomy.md` for full detail.
